Requirements

• 7+ years of professional ML engineering experience, currently working at senior level or above (Senior/Lead/Staff ML Engineer, AI Engineer, or ML/AI Systems Architect).
• Has built and shipped AI or ML systems that ran in production in a real company, not just notebooks or side projects.
• Depth across the AI engineering spine: agentic systems (L3, LangChain/CrewAI/ADK frameworks, orchestration, self-correction), agent reliability and guardrails, MCP; LLM evals (eval harness, LLM-as-judge, hallucination metrics), applied fine-tuning (SFT/LoRA); AI coding tools in the SDLC, LLM observability, A/B experiment design.
• Can explain why a modeling or architecture decision was made, not just how it was implemented, and can diagnose and critique someone else's work live.
• Strong technical communication: comfortable leading a live session and writing clear, specific review feedback.
• Strong English C1+ — instruction and review are in English for a US-based audience.
• Comfortable using AI tools in day-to-day technical work.

Work Location